Zeigt Titel in Data Science

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?

Celebrated data-driven growth leader Lillian Pierson delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.

One key responsibility of product designers and UX practitioners is to conduct formal and informal research to clarify design decisions and business needs. But there’s often mystery around product research, with the feeling that you need to be a research Zen master to gather anything useful. But anyone can conduct product research. With this quick reference guide, you’ll learn a common language and set of tools to help you carry out research in an informed and productive manner.

Microsoft Power Platform for Dummies covers the essentials you need to know to get started with Microsoft Power Platform, the suite of business intelligence applications designed to make your enterprise work smarter and more efficiently.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

Go in Action is for any intermediate-level developer who has experience with other programming languages and wants a jump-start in learning Go or a more thorough understanding of the language and its internals. This book provides an intensive, comprehensive, and idiomatic view of Go. It focuses on the specification and implementation of the language, including topics like language syntax, Go's type system, concurrency, channels, and testing.

Docker in Action teaches listeners how to create, deploy, and manage applications hosted in Docker containers. After starting with a clear explanation of the Docker model, you will learn how to package applications in containers, including techniques for testing and distributing applications. You will also learn how to run programs securely and how to manage shared resources. Using carefully designed examples, the book teaches you how to orchestrate containers and applications from installation to removal.

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

This book consists of 6 titles, namely: Assembly Language: The Ultimate Guide to Programming and Virtual Machines. Computer Science: The Complete Guide to Principles and Informatics. Cyber Security: Beginners’ Guide to Hacking, Phishing, Social Engineering, and Malware. Databases: System Concepts, Designs, Management, and Implementation. Operating Systems: Concepts to Save Money, Time, and Frustration. Website Development: Web Design Skills for Beginners

Veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data.

In Generative AI: Navigating the Course to the Artificial General Intelligence Future, Martin Musiol delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space.

This book is for people who are serious about how they can improve how their organizations run and how they can make their next large transformation project a success. It is for the process and architecture practitioners who run their programs for years and don’t get the visibility that they deserve. It is for the analysts who want to switch their practices to a data-driven approach (while not forgetting the human contributions in the analysis) and for whom the words “Digital Gemba” sound good.

In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best-create physical products-with what digitals do best-use algorithms and AI to parse expansive, interconnected datasets-to make strategic connections that would otherwise be impossible.

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning initiatives, aka predictive AI projects, from conception to deployment.

To succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery.

An expert on China’s global infrastructure expansion provides an urgent look at the battle to connect and control tomorrow’s networks. From the ocean floor to outer space, China’s Digital Silk Road aims to wire the world and rewrite the global order. Taking readers on a journey inside...

This audiobook will help you get ready for the changes coming in the years ahead. Listen now. Packed with expert insights, the book addresses critical questions: How will AI alter employment, education, and global geopolitics? What ethical dilemmas will arise as humans interlace with AI through cyborgs and synthetic biology? Can we prepare for superintelligence and its utopian—or dystopian—outcomes?

The Internet of Things is a networked world of connected devices, objects, and people. In this book Samuel Greengard offers a guided tour through this emerging world and how it will change the way we live and work. Greengard explains that the Internet of Things (IoT) is still in its early stages. Smartphones, cloud computing, RFID (radio-frequency identification), technology, sensors, and miniaturization are converging to make possible a new generation of embedded and immersive technology.

The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems.